Spatial architectures of somatic mutations in normal prostate, benign prostatic hyperplasia and coexisting prostate cancer

Abstract

This study aimed to identify somatic mutations in nontumor cells (NSMs) in normal prostate and benign prostatic hyperplasia (BPH) and to determine their relatedness to prostate cancer (PCA). From 22 PCA patients, two prostates were sampled for 3-dimensional mapping (50 normal, 46 BPH and 1 PCA samples), and 20 prostates were trio-sampled (two normal or BPH samples and one PCA sample) and analyzed by whole-genome sequencing. Normal and BPH tissues harbored several driver NSMs and copy number alterations (CNAs), including in FOXA1, but the variations exhibited low incidence, rare recurrence, and rare overlap with PCAs. CNAs, structural variants, and mutation signatures were similar between normal and BPH samples, while BPHs harbored a higher mutation burden, shorter telomere length, larger clone size, and more private NSMs than normal prostates. We identified peripheral-zonal dominance and right-side asymmetry in NSMs, but the asymmetry was heterogeneous between samples. In one normal prostate, private oncogenic RAS-signaling NSMs were detected, suggesting convergence in clonal maintenance. Early embryonic mutations exhibited two distinct distributions, characterized as layered and mixed patterns. Our study identified that the BPH genome differed from the normal prostate genome but was still closer to the normal genome than to the PCA genome, suggesting that BPH might be more related to aging or environmental stress than to tumorigenic processes.

Fig. 1. Study design and age-mutation correlations in normal and BPH samples.

a Graphical summary showing 22 prostate tissues (20 cases with trio sampling and two cases with extensive 3D spatial sampling), followed by microdissection and low-input DNA whole-genome sequencing (WGS) and deep-panel sequencing. b Clone sizes, estimated from the peak of the variant allele frequency (VAF) in normal, BPH, and PCA samples. c The mutation burden increased with age in both normal prostate and BPH clones (shaded area: 95% confidence interval). The regression model for the normal tissue shows a slope of 16 mutations per year per clone with an R² of 0.10. The slope of BPH samples (43.4 mutations/year/clone with an R² of 0.36) was higher than that of normal samples. d Summary of genomic profiles between normal and BPH samples. Asterisk (*) indicates age-corrected regression p value. e Aging, APOBEC, ROS, and HRD mutational signatures in normal, BPH, and prostate cancer samples. f Comparison of mutational signature proportions between normal, BPH, and prostate cancer samples. n.s., p > 0.05.

Fig. 2. Subclonal genomic architectures of normal prostate and BPH.

a Variant allele frequency (VAF) distribution grouped by the mutation clusters. BPH shows a higher VAF of PC mutations than normal tissues (p = 0.026). b Proportion of PS mutations in normal and BPH samples. BPH showed a higher PS proportion than normal tissues (chi-square p = 0.0129). c Example of private clonal cell cluster expansion in BPHs. In PCA-198, both BPHs (N1 and N2) show PC expansion with different BCOR indels.

Fig. 3. Spatial sequencing reveals intraprostate genomic heterogeneity.

a, b Sampling information and VAF distribution of PCA-28 (a) and PCA-49 (b). c–f BPHs in PCA-28 show significantly higher mutation burden and shorter telomere length than normal cells. Green: normal; Brown: BPH (c). Significant differences in mutation burden by zonal distribution (d) (H-test p = 0.0436) and by left-right sidedness (e) (p = 0.0025). f Proportions of private subclones in left and right BPHs (chi-square p = 0.0108). g Somatic alterations of PCA-49. The right side has significantly more somatic alterations (31.6%) than the left side (5.3%, p = 0.0364). h Distribution of convergent RTK-RAS pathway mutations in PCA-49. i Large-scale chromosomal alterations in PCA-49. Red: gain. Blue: loss.

Fig. 4. Early embryonic mutations in the prostate and reconstruction of ancestral lineages.

a, b Pattern and allele frequency of early embryonic mutations in PCA-28 (a) and PCA-49 (b) with the disease types displayed in the bottom plots. PCA-28 was divided into three groups: lineage-like 1, lineage-like 2, and early mutation-absent; PCA-49 was divided into four groups: lineage-like 1, 2, and 3 and early mutation-absent. c, d Graphical distribution, lineage reconstruction, and lineage progression by color-coded representation of the ancestral mutations in PCA-28 (c) and PCA-49 cases (d). Each unit of the sample coordinate map represents a sample.